Senior / Staff Robotics and Controls Engineer

Reports to: Manager of Robotics and Controls

Workplace Type: Hybrid (onsite average of 3 days/week in Santa Cruz and the

new Bay Area office near West Menlo Park).

At Capstan Medical, we’re building one of the most exciting and innovative companies in medtech-developing a first-of-its-kind robotic platform for minimally invasive heart valve treatment. Our team combines surgical robotics, catheter-based delivery, and next-generation implants to transform complex procedures into safer, lower-stress solutions for patients and clinicians alike. As a highly collaborative, hands-on team, we move fast, wear multiple hats, and believe the best ideas can come from anyone.

Based in Santa Cruz, our unique workspace blends cutting-edge Bay Area innovation with a lifestyle-driven environment near trails, beaches, and open space-creating the perfect place to do meaningful, career-defining work.

What You’ll Do:

• Design, implement, and verify robotic control algorithms for Capstan's

  catheter-based surgical platform - kinematics, dynamics, teleoperation,

  and motion control.

• Develop forward and inverse kinematic models for continuum and tendon-

  driven mechanisms, and validate them against real-world data.

• Build trajectory engines, drive modes, and constraint-aware motion

  algorithms that translate surgeon intent into safe, precise catheter motion.

• Design and execute characterization studies on actuators, tendon

  transmissions, and full system performance; translate experimental results

  into models, parameters, and acceptance criteria.

• Define algorithm-level performance specifications and hazard-driven fault

  detection thresholds; partner with Systems and Quality to support design

  verification and regulatory submissions

• Translate clinical and user needs into design requirements, prototype

  rapidly on real hardware, and carry features through verification to

  product launch

• Drive technical direction for path planning, catheter control, or robotics

  algorithms across multiple hardware programs (increased level of

  architectural ownership and cross-program scope for Staff)

• Mentor engineers on the team, lead design reviews, and contribute to

  hiring and onboarding (increased level of mentorship for Staff)

• Document your work through design reviews and released DHF

  documentation, and identify gaps and pitch in as needed to keep the team

  moving

Strongly Preferred:

• Strong foundation in robot kinematics and dynamics - forward/inverse kinematics, Jacobians, rigid-body dynamics, and ideally continuum, concentric tube, or tendon-driven systems
• Fluent with classical and modern control -- PID, feedforward, model-based, optimal/MPC, impedance/admittance -- and the judgment to know when each is appropriate
• Hands-on experience implementing control algorithms in modern C++ (14/17/20) for real-time, safety-critical systems, with Python for rapid prototyping, data analysis, and tooling
• Motion planning and trajectory generation experience - constrained nonlinear optimization, collision-aware planning, or task-space control paradigms
• State estimation and sensor fusion experience - Kalman/EKF/UKF, particle filters, or nonlinear observers, with a working understanding of noise models and sensor calibration
• Comfortable characterizing real electromechanical systems on the bench; you can design the experiment, run it, analyze the data, and turn it into a model.
• Close-to-hardware sensibility: encoders, motor controllers, force sensors, brakes, IMUs -- you understand the gap between textbook systems and real ones
• Strong object-oriented design instincts, with the discipline to factor algorithm code so it can be unit-tested, reviewed, and maintained as the team scales
• Medical robotics or safety-critical systems background -- you know why "it works in sim" or "it works most of the time" isn't good enough
• Understanding of how early design decisions cascade into downstream cost; ability to make smart calls on clinical workflow, regulation, and risk management to save time and effort later

Requirements:

• BS/MS in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or equivalent; MS or PhD preferred
• 5+ years (Senior) or 8+ years (Staff) of hands-on robotics or controls development; PhD with directly relevant research or projects can offset some industry experience
• Track record of shipping robotic control algorithms in real production systems, ideally end-to-end from concept to production, IDE/clinical use, or FDA-cleared product
• Experience navigating ambiguity in early- and mid-stage development while delivering concrete, testable results
• Experience with medical device development process - design control, risk management, design verification - or equivalent experience in another safety-critical regulated domain
• Demonstrated ability to derive math from first principles and implement it in working code; we want the whiteboard and the IDE in the same person
• Strong written and verbal communication, meaning that you can write a clear design doc, defend a design review, and explain a controller to a non-controls engineer
• Comfortable working hands-on in a lab environment alongside hardware, benchtop fixtures, animals (preclinical), and clinicians
• Ability to work in a hybrid work environment, working onsite an average of 3 days a week, in a mix of our Santa Cruz HQ and our new Bay Area office near West Menlo Park.

Bonus

• Flexible robotics experience -- concentric tube robots, tendon-driven, soft, or other compliant manipulators
• Surgical robotics or another regulated, safety-critical robotics background
• Sensing, electromagnetic tracking, or other catheter-tip localization experience
• Experience integrating fluoroscopy, ultrasound, or CT imaging into robotic guidance, registration, or visual servoing
• ROS1 or ROS2 experience in production systems, with an understanding of its real-time tradeoffs
• Working knowledge of regulatory standards (FDA, IEC 62304, ISO 14971, IEC 60601) and how they shape algorithm and architecture decisions
• Experience with simulation environments (Drake, MuJoCo, Isaac Sim, or custom) for development, regression, and verification
• Familiarity with QNX or real-time Linux: you don't have to own the stack, but you should understand the constraints it places on your algorithms
• Track record of technical leadership and mentorship at a comparable medical robotics or capital equipment company